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        "author": "Akshay Raj Gollahalli",
        "author_email": "akshay@gollahalli.com",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering"
        ],
        "description": "# Spike Encoders\n\n| Branch | Codecov | CI | Requirements |\n|--------|---------|---------------------------------------------------------------------------------------------------------------------------------------|--------------|\n| Master | Soon.. | [![Build Status](https://travis-ci.org/akshaybabloo/Spikes.svg?branch=master)](https://travis-ci.org/akshaybabloo/Spikes) | [![Updates](https://pyup.io/repos/github/akshaybabloo/Spikes/shield.svg)](https://pyup.io/repos/github/akshaybabloo/Spikes/) |\n\nSpike encoders for Spiking Neural Network.\n\nThis package consists of two types of spike encoders for spatio-temporal data:\n\n1. Threshold Based Representation (TBR) encoder\n2. Bens Spiker Algorithm (BSA) encoder\n\n<!-- TOC -->\n\n- [Data](#data)\n- [Instillation](#instillation)\n- [Example](#example)\n- [Contribution](#contribution)\n- [Issues](#issues)\n\n<!-- /TOC -->\n\n## Data\n\nThe data given to the encoders are spatio-temporal. Each sample is one `csv` file. In each file, every column is a feature and the rows are time points.\n\nFor example each file given in the [Data](https://github.com/akshaybabloo/Spikes/tree/master/Data) folder had 128 rows and 14 columns, 14 columns are the features and 128 columns are the data points.\n\n## Instillation\n\n```\npython setup.py install\n```\n\n## Example\n\n```python\nfrom spikes import encoder\nfrom spikes.utility import ReadCSV\n\ndata = ReadCSV('Data').get_samples()['samples']\n\nbsa = encoder.BSA(data)\nprint(bsa.get_spikes())\n\ntbr = encoder.TBR(data)\nprint(tbr.get_spikes())\n```\n\n## Contribution\n\nAll contributions are welcome.\n\n## Issues\n\nIssues can be opened through Github's [Issues](https://github.com/akshaybabloo/Spikes/issues) tab.\n\n\n",
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        "keywords": "Spiking Neural Network spike encoder",
        "license": "BSD-3-Clause",
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